Introduction to computational health informatics / by Arvind Kumar Bansal, Javed Iqbal Khan, S. Kaisar Alam.
Material type:
TextSeries: Publisher: Boca Raton, FL : CRC Press, [2020]Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781000761436; 1000761436; 9781003003564; 1003003567; 9781000761597; 1000761592Subject(s): Medical informatics -- Study and teaching | MEDICAL / Administration | COMPUTERS / Database Management / Data Mining | MEDICAL / GeneralDDC classification: 610.285 LOC classification: R859 | .B36 2020Online resources: Taylor & Francis | OCLC metadata license agreement Summary: This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and clinical perspectives. This book prepares computer science students for careers in computational health informatics and medical data analysis. Features Integrates computer science and clinical perspectives Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development
This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and clinical perspectives. This book prepares computer science students for careers in computational health informatics and medical data analysis. Features Integrates computer science and clinical perspectives Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development
OCLC-licensed vendor bibliographic record.